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Announce: Computational Methods meeting

Andy Zaayenga andy.zaayenga at lab-robotics.org
Sat Oct 30 15:12:59 EST 2004

Announce: Computational Methods meeting

Laboratory Robotics Interest Group
Mid Atlantic Chapter Meeting
Computational Methods

Date: Wednesday, November 3, 2004
Place:  Somerset Marriott Hotel, 110 Davidson Ave., Somerset, NJ 08873
Itinerary: Social Period - 4:00pm to 6:00pm
Meeting & Presentations - 6:00pm to 8:30pm
Registration: http://lab-robotics.org/member/meetings.asp?rid=1
There is no fee to attend the meeting, but please register to insure there
is enough food and seating for all. There will be drawings from the web
registrants for door prizes. 

Agenda: Computational chemistry and molecular modeling have emerged as
obligatory tools in the drug discovery armentarium under the broad aegis of
CHEMINFORMATICS, loosely defined as follows: "mixing of information
resources to transform data into information, and information into
knowledge, for the intended purpose of making better decisions faster in the
arena of drug lead identification and optimization
(http://www.warr.com/wzarc00.html). As such, the field has benefited from an
extraordinary explosion in popularity and awareness. To wit, citation of the
term (via Google) has increased from 700 times in July 2000 vs 35,000 times
in July 2004 (http://www.molinspiration.com/chemoinformatics.html). LRIG is
pleased to offer this session, which will strive to present the 'flavors' of
Computational Chemistry, and its associated infrastructure for data
management, to our members.

Food and refreshments will be available FREE OF CHARGE during the Exhibition
and Social Period.

Presentation: PREDICT modeling and in silico screening for GPCR: From amino
acid sequence to the clinic
Sharon Shacham(1)1, Yael Marantz(2), Silvia Noiman(2), Oren, M Becker(2),
and Michael, G Kauffman(1)
(1) Predix Pharmaceuticals, 10K Gill St, Woburn, MA 01801, (2) Predix
Pharmaceuticals Ltd, 3 Hayetsira St, Ramat Gan, 52521, Israel

GPCRs constitute a major family of drug targets, involved in many
physiological responses. However, the use of structure-based drug discovery
methods for GPCRs has been limited by the fact that only one x-ray structure
of a non-drugable GPCR (i.e. bovine rhodopsin) is known. The homology
between rhodopsin and other GPCRs is very low and existing structural
information is not sufficient for accurate structure prediction and drug
discovery or optimization using standard homology modeling. Predix
Pharmaceuticals has developed a suite of algorithms that permit the
structure-based discovery and optimization of drug candidates binding to
GPCRs and Ion Channels. Predix' discovery platform includes a novel
technology for modeling the 3D structure of any GPCR based solely on its
amino-acid sequence (PREDICT); The model is then used initially for
in-silico screening against any library. The 50-200 virtual hits with best
scores are sent for affinity studies in vitro. In several programs the
initial hits were converted into early drug candidates using Predix's
ICELR-3D platform, which includes novel algorithms for the prediction of
oral bioavailability, GPCR selectivity, and potential for QTc prolongation
through HERG ion channel binding. The accuracy of the PREDICT models, was
extensively validated, including: (a) agreement with rhodopsin X-ray
structure; (b) reproduction of site-directed mutagenesis data: (c) PREDICT
models yield novel hits with nanomolar activity in binding assays in 6
different programs (d) PRX-0023, a novel, non-azapirone lead clinical
candidate 5-HT1A agonist with preclinical activity in anxiety and attention
deficit hyperactivity disorder successfully completed Phase I clinical

Presentation: Strategies for analyzing discovery data
Glenn J. Myatt, Paul Blower, Kevin Cross, Chihae Yang 
Leadscope, 1393 Dublin Road, Columbus, Ohio 43215

The presentation will review different approaches for analyzing data sets of
chemical structures and biological activity data. Techniques for becoming
familiar with the data set will be described including methods for assessing
structural diversity. Methods for integrating, assessing and filtering the
data set prior to analysis will be described. Depending on the nature of the
data set (size, data distribution, and structural diversity) different
methods for analyzing the data should be adopted. The presentation will
review these alternative chemical structure-based data analysis approaches.
Trends in the data may be further qualified by searching other databases,
such as collections of toxicity data to determine any known safety
liabilities with the chemical series identified. Case studies will be used
to illustrate this process.

Presentation: A High-Performance Workflow Automation System for Drug
Dr. Srini Chari; General Manager, Solutions 
TurboWorx, Inc.

Many scientific problems are solved by analyzing large quantities of data
using multiple compute-intensive applications linked together in complex
ways. In pharmaceutical research and development, identifying lead compounds
requires first computing various properties for large numbers of individual
compounds, filtering the compounds based on specific property-based
criteria, and performing further modeling and simulation calculations.
Today's networked computing environments can be excellent platforms for
processing these computational workflows because they make available large
numbers of highly capable individual machines. However, the job of creating,
managing, and deploying distributed workflows is daunting to most users.
Very few of them are able to write robust programs or scripts that deal with
issues such as authenticating users, selecting proper machines to run given
applications, moving data between applications, and handling application
errors and hardware failures. 
In this talk we will address solutions effectively address all these issues
and more. Users benefit from reduced development effort and execution time,
leading to increased personnel productivity and higher analysis throughput.
The TurboWorx Enterprise system allows computational workflows to be built
visually, using boxes to represent application and data access tasks, and
using directed lines to specify task dependencies and data paths. At
runtime, the system dynamically decomposes each workflow job into its
constituent tasks and arranges for task execution on appropriate compute
nodes. The system also coordinates all the task executions in order to honor
task dependencies and to ensure efficient data transfer along specified data
This system also provides an open, extensible environment that includes
visual tools that make it easy to add to the system any application that can
be run from a command line. Furthermore, it offers rich support for fault
tolerance, custom user authentication, data parallelism, and flow controls.
To those scientists who need to analyze large amounts of data using complex
computational pipelines, TurboWorx Enterprise will be an invaluable

Updated information may be found on our web site at:

There is always a Job posting board at the meeting. Please encourage your
recruiters to give you material to post and distribute. Openings may also be
posted at:

Upcoming Meetings in the LRIG Mid Atlantic chapter

Our annual "Automated Sample Management, Storage and Retrieval" meeting is
January 13, and will feature new research from Chris Lipinski as well as
speakers from Merck, Bristol-Meyers Squibb, and AstraZeneca.

We are also offering a new feature at the January meeting - a free workshop
in LabView!

Details at:

Thank you for your support. We hope to see you there!

Andy Zaayenga, 
on behalf of
The LRIG Mid Atlantic Officers

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